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All Journal Journal of Vocational, Informatics and Computer Education
Muafan, Wildan
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Computer Science & IT Education Other

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Analysis of the Impact of Artificial Intelligence Technology on the Development of Students’ Academic Writing Skills in the Digital Learning Era Hidayat, Nur; Muafan, Wildan; Nurjannah, Elma; Akhmad Affandi; Rosidah
Journal of Vocational, Informatics and Computer Education Vol 3, No 2 (2025): Desember 2025
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/csm13a29

Abstract

The rapid advancement of Artificial Intelligence (AI) has transformed academic practices, particularly in supporting the development of students’ academic writing. However, empirical evidence explaining how AI utilization, automatic feedback, and personalized learning contribute to writing performance in higher education remains limited. This study examines the effects of AI utilization, AI-based automatic feedback, and AI-driven personalized learning on Students’ Academic Writing Skills (SAWS). Using an explanatory quantitative approach with a cross-sectional design, data were collected from 88 Indonesian university students through purposive sampling. Partial Least Squares–Structural Equation Modeling (PLS-SEM) was employed to evaluate the measurement and structural models. The findings show that Automatic Feedback Based on AI (AFBAI) is the strongest predictor of SAWS (β = 0.531; p = 0.000). The Utilization of AI Technology (UAIT) also has a significant positive effect (β = 0.290; p = 0.007), indicating that frequent use of AI tools contributes to improved writing skills. Conversely, Personalized Learning Based on AI (PLBAI) has no significant direct effect (β = 0.053; p = 0.350). The structural model demonstrates substantial predictive power with an R² value of 0.660. AI technologies play an essential role in enhancing academic writing performance, especially through automated feedback and consistent utilization. However, AI-driven personalized learning systems still require further optimization and deeper user engagement to meaningfully support the development of complex writing competencies.
Co-Authors Akhmad Affandi Nur Hidayat Nurjannah, Elma Rosidah